prep for search

main.py

@@ -71,14 +71,14 @@ if __name__ == "__main__":
     )
 
     save_img_callback = SaveImageCallback(
-        save_interval=1,
+        save_interval=0,
         final_dir="out",
     )
 
     # Initialize data loader with parsed arguments
     # named_data_loader also has grayscale extras. TODO: remove unnamed
     train_dataloader = create_dataloader(
-        N=1e8,
+        N=1e7,
         batch_size=args.bs,
         shuffle=True,
         num_workers=args.num_workers,

search.py

@@ -20,7 +20,7 @@ NUM_JOBS = 100
 # Define the ranges or sets of values for each hyperparameter
 # alpha_values = list(np.round(np.linspace(2, 4, 21), 4))
 # learning_rate_values = list(np.round(np.logspace(-5, -3, 21), 5))
-learning_rate_values = [1e-3]
+learning_rate_values = [1e-2, 1e-3]
 alpha_values = [0, 1, 2]
 widths = [64, 128, 256, 512]
 # learning_rate_values = [5e-4]